Endogenous growth and entropy

This paper offers novel insights regarding the role of complexity in both the transitional and the long-run dynamics of the economy. We devise an endogenous growth model that encompasses long-run economic change building on the concept of entropy as a time-varying state-dependent complexity effect. We show that the empirical evidence supports entropy as an 'operator' of the complexity effect. It also suggests that part of the modern innovations have a stabilizing role in the complexity of the economies, as the 'operator' levels off despite the continuous increase in the measure of technological varieties. The model features endogenous growth, with null or small scale effects, or stagnation, in the long run. The model can replicate well the take-off after the industrial revolution and the productivity slowdown in the second half of the XXth century. Long-run scenarios based on in-sample calibration are discussed, and may help explain (part of) the growth crises affecting the current generation.